车辆动力学性能参数估计方法研究
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摘要
随着运营速度的不断提高,车辆在高速状态下的动态特性相对于低速状态存在显著不同,如轮轨作用、气流作用、弓网作用的加强,从而诱发振动加剧,磨耗加快、噪声加强等恶劣服役环境。这些环境因素对车辆服役的稳定性、平稳性、可靠性及其安全性提出了更高的要求,同时也对车辆维护检修提出了新要求,带来了新的挑战。为此,深化研究车辆在复杂环境下的服役性能及其演变规律,具有重要的工程意义。车辆的力学性能取决于车辆的结构参数,一定程度上,研究服役性能的演变规律就是研究性能参数的演变规律。研究性能参数随服役里程的演变规律及其参数演变与动力学性能蜕变之间的关系,最为重要环节正是性能参数的估计研究。
尽管如此,但是目前有关车辆动力学性能参数估计的研究在国内外均处于起步阶段,参数估计理论及其技术还不成熟,研究成果及其论文相对较少。在力学模型合理简化,高维力学模型到高维概率模型转化,车辆性能参数估计的概率模型、结构特点分析、信息流特点分析,用于车辆性能参数估计的概率理论、参数估计模型及其估计方法的适应性上,均没有系统阐述。同时,随着运营速度的不断提高,对性能参数的估计精度、估计参数的数量、实时性等关键性能指标上也提出了更高要求。
因此,本文以车辆动力学性能参数估计的具体过程为论文的研究线索；以参数估计相关模型的构建、参数估计理论的分析推导、以及参数估计模型、参数估计理论及其模型的理论与试验验证为主要研究内容；以提高参数估计方法的适应性,参数估计精度、参数估计的快速性等关键性能指标为主要研究目标。针对动力学性能参数估计的这些关键理论与技术问题,本文做了一些十分初浅的研究工作。相关工作主要体现在：
(1)梳理了参数估计理论及其方法在国内外的研究现状,分析了不同参数估计方法的根本技术特点,指出了不同参数估计方法的优势和不足。分析了车辆对象的结构特点,车辆动力学性能参数估计是一个多参数、高维状态、初值敏感、多模态的复杂非线性问题。在此基础上,指出了基于混合滤波理论的参数估计方法是车辆性能参数估计的主要发展方向,能够充分利用卡尔曼滤波处理线性状态滤波问题的独特优势,能够充分利用粒子滤波、切片高斯混合滤波处理非线性、初值敏感等滤波问题的独特优势,在方法上形成优势互补；
(2)通过经典力学原理建立了车辆横向力学模型。分析了四种连续状态离散化方法的技术特点,其中,定义法对车辆力学模型的离散化具有很强的适应性,由离散频率确定离散精度,建立了状态转移方程。引入了参数估计的辅助进化方程。通过传感器配置,建立了观测方程。将状态转移方程、参数的辅助进化方程、观测方程进行融合,构建了增广状态空间的参数估计概率模型。在此基础上,分析了参数估计概率模型的信息流结构特点,指出了车辆性能参数估计的概率模型是一个高维条件线性模型；
(3)在分析了卡尔曼滤波、扩展卡尔曼滤波、粒子滤波、边缘粒子滤波的基本理论和技术特点的基础上,分别建立了基于扩展卡尔曼滤波的车辆动力学性能参数估计模型,建立了基于边缘粒子滤波的车辆动力学性能参数估计模型。分别从理论、试验角度对参数估计的方法和模型进行了验证和性能对比；
(4)在对传统边缘粒子滤波改进的基础上,建立了基于改进边缘粒子滤波的参数估计模型,应用算例验证了模型的有效性,并与基于边缘粒子滤波的参数估计方法进行了比较；
(5)在梳理低维切片高斯混合滤波基本理论的基础上,应用狄拉克树和高斯单元缩减理论将切片高斯混合滤波理论由低维情况发展到高维情况,建立了基于切片高斯混合滤波的参数估计模型。通过算例验证了模型的有效性,并与基于边缘粒子滤波和改进边缘粒子滤波的参数估计方法进行了性能比较。
Service environment, such as increased vibration, accelerated wear and tear, enhanced noise etc, have become more complicated with the continuous improvement of speed because the dynamic characteristics of train at high speed are significantly different from some at low speed, especially, wheel-rail interaction force, air role and bow net-effect have further strengthened.The stability, reliability, security of high-speed train in service will put forward higher requirements in response to these environmental factors,at the same time, The maintenance and nursing of high-speed trai have proposed new requirements. Therefore, the deepening study of service performance under its evolution is of great significance. Since the mechanical properties of high-speed trains depend on structural parameters, to some extent, the study of service performanc evolution is equel to study parameters evolution. During the process of studying relationship between arameters with their evolutio and Miles of service, between dynamic parameter and performance degradatio, the most important step is parameter identification.
At present, the relevant study of parameter identification of high-speed train at home and abroad is in the initial stage, the parameter identification theory and technology is also not mature, there is less research and thesis. Many key technologies, such as reasonable simplication of mechanical model, conversion from high-dimensional mechanical model to high-dimensional probability model, analysis of parameter identification and structural features of the probabilistic model and information flow, probability theory for parameter identification, suitabilities between parameter identification model and identification method did not elaborate on the system. At the same time, the key performance indicators, as the accuracy, quantity, timeliness of parameter identification etc put forward higherand newer requirements. Therefore, this study identifies the specific process of parameters identification for clues, regards the relevant model of parameter identification, parameter identification theory and its derivation, parameter identification model, theory and experimental verification of parameter identification theory and its model as the main study contents, regards performance indicators improvement of adaptability, identification accuracy, speed and etc as the main targets.In response to these key issues, this paper carries out related research work, mainly reflected in:
(1) The characteristics, advantages and disadvantages of different physical parameters identification method are analyzed on the base of research status about physical parameters and method at home and abroad. The parameter identification of high-speed train is a multiparameter, high-dimensional state, the initial value sensitive, complex multi-modal nonlinear problems, through analysis of the structural characteristics of high-speed train. The main development direction that parameter identification of high-speed train is based on mixture filtering theory is pointed out, which can make full use of the unique advantages sloving linear state inference by the Kalman filter and unique advantages of particle filter, sliced Gaussian mixture filter for nonlinear Problem, initial treatment of sensitive issues.the result is the formation of complementary advantages.
(2) The mechanical model of high-speed train is constructed by mechanics,On the base of technical features analysis of the four discrete methods for continuous, the defined method is highly adaptable mechanical model of high-speed train and further to determine the discrete frequency,fianally the state transition equation is established. The supporting evolutionary equation of parameter identification is introduced. The observation equation is constructed by sensor configuration. On this basis, probability model of parameter identification is a high-dimensional conditionally linear model through analysis of information flow structure of the probabilistic model.
(3) The methods and models of parameter identification based on extended kalman filfter and Rao-Blackwellised particle filter are proposed on the base of the analysis of the basic theory and technical characteristics.the methods and theory of parameter identification are tested and verified from the view of theoretical and experimental poin.In another aspect, performance comparison is carried ou.
(4) The method and model of parameter identification based on modified Rao-Blackwellised particle filter is proposed on the base of modification and improvement of traditional Rao-Blackwellised particle filter.An example to verify the validity of the method is executived. Parameters identification performance based on modified Rao-Blackwellised particle filter are compared to traditional Rao-Blackwellised particle filter.
(5) The parameters identification method and model based on the sliced gassian mixture filter modified from the low dimension to high-dimensional case by the dirac-mixture tree and gaussian mixture reduction on the base of carding of basical Gaussian mixture filter.The numerical results verify the effectiveness of the method. The parameters identification performance based on the sliced gassian mixture filter is compared to Rao-Blackwellised particle filter and modified Rao-Blackwellised particle filter.
尽管如此,但是目前有关车辆动力学性能参数估计的研究在国内外均处于起步阶段,参数估计理论及其技术还不成熟,研究成果及其论文相对较少。在力学模型合理简化,高维力学模型到高维概率模型转化,车辆性能参数估计的概率模型、结构特点分析、信息流特点分析,用于车辆性能参数估计的概率理论、参数估计模型及其估计方法的适应性上,均没有系统阐述。同时,随着运营速度的不断提高,对性能参数的估计精度、估计参数的数量、实时性等关键性能指标上也提出了更高要求。
因此,本文以车辆动力学性能参数估计的具体过程为论文的研究线索；以参数估计相关模型的构建、参数估计理论的分析推导、以及参数估计模型、参数估计理论及其模型的理论与试验验证为主要研究内容；以提高参数估计方法的适应性,参数估计精度、参数估计的快速性等关键性能指标为主要研究目标。针对动力学性能参数估计的这些关键理论与技术问题,本文做了一些十分初浅的研究工作。相关工作主要体现在：
(1)梳理了参数估计理论及其方法在国内外的研究现状,分析了不同参数估计方法的根本技术特点,指出了不同参数估计方法的优势和不足。分析了车辆对象的结构特点,车辆动力学性能参数估计是一个多参数、高维状态、初值敏感、多模态的复杂非线性问题。在此基础上,指出了基于混合滤波理论的参数估计方法是车辆性能参数估计的主要发展方向,能够充分利用卡尔曼滤波处理线性状态滤波问题的独特优势,能够充分利用粒子滤波、切片高斯混合滤波处理非线性、初值敏感等滤波问题的独特优势,在方法上形成优势互补；
(2)通过经典力学原理建立了车辆横向力学模型。分析了四种连续状态离散化方法的技术特点,其中,定义法对车辆力学模型的离散化具有很强的适应性,由离散频率确定离散精度,建立了状态转移方程。引入了参数估计的辅助进化方程。通过传感器配置,建立了观测方程。将状态转移方程、参数的辅助进化方程、观测方程进行融合,构建了增广状态空间的参数估计概率模型。在此基础上,分析了参数估计概率模型的信息流结构特点,指出了车辆性能参数估计的概率模型是一个高维条件线性模型；
(3)在分析了卡尔曼滤波、扩展卡尔曼滤波、粒子滤波、边缘粒子滤波的基本理论和技术特点的基础上,分别建立了基于扩展卡尔曼滤波的车辆动力学性能参数估计模型,建立了基于边缘粒子滤波的车辆动力学性能参数估计模型。分别从理论、试验角度对参数估计的方法和模型进行了验证和性能对比；
(4)在对传统边缘粒子滤波改进的基础上,建立了基于改进边缘粒子滤波的参数估计模型,应用算例验证了模型的有效性,并与基于边缘粒子滤波的参数估计方法进行了比较；
(5)在梳理低维切片高斯混合滤波基本理论的基础上,应用狄拉克树和高斯单元缩减理论将切片高斯混合滤波理论由低维情况发展到高维情况,建立了基于切片高斯混合滤波的参数估计模型。通过算例验证了模型的有效性,并与基于边缘粒子滤波和改进边缘粒子滤波的参数估计方法进行了性能比较。
Service environment, such as increased vibration, accelerated wear and tear, enhanced noise etc, have become more complicated with the continuous improvement of speed because the dynamic characteristics of train at high speed are significantly different from some at low speed, especially, wheel-rail interaction force, air role and bow net-effect have further strengthened.The stability, reliability, security of high-speed train in service will put forward higher requirements in response to these environmental factors,at the same time, The maintenance and nursing of high-speed trai have proposed new requirements. Therefore, the deepening study of service performance under its evolution is of great significance. Since the mechanical properties of high-speed trains depend on structural parameters, to some extent, the study of service performanc evolution is equel to study parameters evolution. During the process of studying relationship between arameters with their evolutio and Miles of service, between dynamic parameter and performance degradatio, the most important step is parameter identification.
At present, the relevant study of parameter identification of high-speed train at home and abroad is in the initial stage, the parameter identification theory and technology is also not mature, there is less research and thesis. Many key technologies, such as reasonable simplication of mechanical model, conversion from high-dimensional mechanical model to high-dimensional probability model, analysis of parameter identification and structural features of the probabilistic model and information flow, probability theory for parameter identification, suitabilities between parameter identification model and identification method did not elaborate on the system. At the same time, the key performance indicators, as the accuracy, quantity, timeliness of parameter identification etc put forward higherand newer requirements. Therefore, this study identifies the specific process of parameters identification for clues, regards the relevant model of parameter identification, parameter identification theory and its derivation, parameter identification model, theory and experimental verification of parameter identification theory and its model as the main study contents, regards performance indicators improvement of adaptability, identification accuracy, speed and etc as the main targets.In response to these key issues, this paper carries out related research work, mainly reflected in:
(1) The characteristics, advantages and disadvantages of different physical parameters identification method are analyzed on the base of research status about physical parameters and method at home and abroad. The parameter identification of high-speed train is a multiparameter, high-dimensional state, the initial value sensitive, complex multi-modal nonlinear problems, through analysis of the structural characteristics of high-speed train. The main development direction that parameter identification of high-speed train is based on mixture filtering theory is pointed out, which can make full use of the unique advantages sloving linear state inference by the Kalman filter and unique advantages of particle filter, sliced Gaussian mixture filter for nonlinear Problem, initial treatment of sensitive issues.the result is the formation of complementary advantages.
(2) The mechanical model of high-speed train is constructed by mechanics,On the base of technical features analysis of the four discrete methods for continuous, the defined method is highly adaptable mechanical model of high-speed train and further to determine the discrete frequency,fianally the state transition equation is established. The supporting evolutionary equation of parameter identification is introduced. The observation equation is constructed by sensor configuration. On this basis, probability model of parameter identification is a high-dimensional conditionally linear model through analysis of information flow structure of the probabilistic model.
(3) The methods and models of parameter identification based on extended kalman filfter and Rao-Blackwellised particle filter are proposed on the base of the analysis of the basic theory and technical characteristics.the methods and theory of parameter identification are tested and verified from the view of theoretical and experimental poin.In another aspect, performance comparison is carried ou.
(4) The method and model of parameter identification based on modified Rao-Blackwellised particle filter is proposed on the base of modification and improvement of traditional Rao-Blackwellised particle filter.An example to verify the validity of the method is executived. Parameters identification performance based on modified Rao-Blackwellised particle filter are compared to traditional Rao-Blackwellised particle filter.
(5) The parameters identification method and model based on the sliced gassian mixture filter modified from the low dimension to high-dimensional case by the dirac-mixture tree and gaussian mixture reduction on the base of carding of basical Gaussian mixture filter.The numerical results verify the effectiveness of the method. The parameters identification performance based on the sliced gassian mixture filter is compared to Rao-Blackwellised particle filter and modified Rao-Blackwellised particle filter.
引文
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